Learning how network structure shapes decision-making for bio-inspired computing

Abstract:

To better understand how network structure shapes intelligent behavior, we developed a learning algorithm that we used to build personalized brain network models for 650 Human Connectome Project participants. We found that participants with higher intelligence scores took more time to solve difficult problems, and that slower solvers had higher average functional connectivity. With simulations we identified a mechanistic link between functional connectivity, intelligence, processing speed and brain synchrony for trading accuracy with speed in dependence of excitation-inhibition balance. Reduced synchrony led decision-making circuits to quickly jump to conclusions, while higher synchrony allowed for better integration of evidence and more robust working memory. Strict tests were applied to ensure reproducibility and generality of the obtained results. Here, we identify links between brain structure and function that enable to learn connectome topology from noninvasive recordings and map it to inter-individual differences in behavior, suggesting broad utility for research and clinical applications.

https://www.nature.com/articles/s41467-023-38626-y

An algebraic theory to discriminate qualia in the brain

The mind-brain problem is to bridge relations between in higher mental events and in lower neural events. To address this, some mathematical models have been proposed to explain how the brain can represent the discriminative structure of qualia, but they remain unresolved due to a lack of validation methods. To understand the qualia discrimination mechanism, we need to ask how the brain autonomously develops such a mathematical structure using the constructive approach. In the paper the authors show that a brain model that learns to satisfy an algebraic independence between neural networks separates metric spaces corresponding to qualia types.

Another beautiful reading for the weekend:

"Searching for computational zones also dissolves the boundaries between what we think of as biology and technology. At the technological extremes are hypothetical concepts like Dyson structures that would capture all of a star’s energy. If these structures are for computation, then we can figure out the design options afforded by thermodynamic and informational principles. Calculations hint that abundant substellar objects—so-called brown dwarfs, weighing in at a few percent the mass of our sun and a hundred thousand times less luminous—might be better Dyson energy sources for uncomplaining technology, but not for biology with its bothersome requirements for warmth and nutrients."

...

"It may also be the case that blended living systems are the only ones able to discover other living systems. Anything else will simply be incapable of noticing, or uninterested in what it shares the cosmos with. If that is true, we really do exist at the most exciting time for any species that has ever arisen on the Earth."

https://www.scientificamerican.com/article/to-find-life-in-the-universe-find-the-computation/

Tech breakthrough: New hydrogel material can extract unlimited amounts of water from the air • Earth.com
https://www.earth.com/news/new-hydrogel-can-extract-unlimited-amounts-of-water-from-the-air-even-in-deserts/

Sharpened Cosine Distance as an Alternative for Convolutions

У 2020 році Brandon Rohrer у Twitter запропонував альтернативу згорткам — Sharpened Cosine Distance. Цей підхід, за його словами, отримує кращі ознаки, аніж звичайні згоркові шари.

У чому проблема згорток?
Ядро згортки усереднює сигнал, через що можуть втрачатися високочастотні ознаки. Згорка створює репрезентативні ознаки, лише коли ядро та сигнал має два значення, 1-bit.

Навіщо Sharpened Cosine Distance?
Не має такого ефекту як у згортки, за означенням. Може ефективно обробляти ненормалізованих вхідний сигнал. Не потребує функцій активації для формування гарних ознак.

📝 Blog post, part 1: Sharpened Cosine Distance as an Alternative for Convolutions
📝 Blog post: part 2: Sharpened Cosine Similarity
🖥 Імплементація на PyTorch, Keras, Jax

Nonlinear change processes and the emergence of suicidal behavior: A conceptual model based on the fluid vulnerability theory of suicide

"... Newer research implicates the existence of multiple nonlinear change processes among suicidal individuals, some of which appear to be associated with the emergence of suicidal behavior. The cusp catastrophe model provides a useful model for conceptualizing these change processes and provides a foundation for explaining a number of poorly understood phenomena including sudden emergence of suicidal behavior without prior suicidal planning. The implications of temporal dynamics for suicide-focused theory, practice, and research are discussed."

Observation of large scale precursor correlations between cosmic rays and earthquakes

Abstract:

The search for correlations between secondary cosmic ray detection rates and seismic effects has long been a subject of investigation motivated by the hope of identifying a new precursor type that could feed a global early warning system against earthquakes. Here we show for the first time that the average variation of the cosmic ray detection rates correlates with the global seismic activity to be observed with a time lag of approximately two weeks, and that the significance of the effect varies with a periodicity resembling the undecenal solar cycle, with a shift in phase of around three years, exceeding 6 sigma at local maxima. The precursor characteristics of the observed correlations point to a pioneer perspective of an early warning system against earthquakes.

https://arxiv.org/abs/2204.12310
https://arxiv.org/ftp/arxiv/papers/2204/2204.12310.pdf

Photonics experiment resolves quantum paradox
https://phys.org/news/2023-07-photonics-quantum-paradox.html